Peer-based review of medical practitioners has been used in the medical community for decades to generate a substantive review of a practitioner's performance level as well as to assess the level of care which the practitioner has provided. Many peer-based reviews are carried out in response to a medical error (e.g. medical malpractice or misconduct), hindering preventative actions from being taken to avoid medical errors. Furthermore, the duration of a peer-based review may be lengthy due to the large amount of medical data under evaluation as well as the inefficient data management of the organization conducting the review. It is for this reason that many health care organizations are seeking fast and efficient methods of practitioner review.
Attempts have been made, by some health care organizations, to utilize automated statistical analysis to provide fast and efficient assessment of medical practitioners. However, generating substantive reviews of medical practitioners from computerized statistical analysis methods may be difficult due to the complexity of the medical system. Further, such analysis may be limited in its value as the analysis is generally based primarily on statistical inputs. By using computerized statistical analysis without any substantive peer review, health care organizations have been able to increase the efficiency of practitioner review and decrease the cost. However, such efficiency has resulted in sacrificing the quality of the review.